A working method for estimating dynamic shear velocity in the montney formation
Bibliographic record
Abstract
In this paper, we present a customized method for estimating sonic shear velocity (Vs) from compressional velocity (Vp) logs in the Montney Formation, in wells lacking dipole sonic data. Following a multi-scenario analysis that comprised of assessing empirical Vs estimation relations [including lithology, porosity (Ø), and volume of clay (V sh )-based Vs estimation techniques], bivariate statistics, and machine learning, we found that the Greenberg & Castagna (1992) shale lithology constants yield Vs log estimates that best match the measured Montney Formation Vs in our study area, with a regional correlation coefficient of 0.8. We have therefore customized the Vs estimation method in our study to use the Greenberg & Castagna (1992) shale lithology constants. Our working method: •Improves the efficacy of Vs log estimation from Vp logs in the study area •Demonstrates the importance of calibrating empirical relations for Vs estimation to a specific formation, and •Provides a more accurate complementary Vs log dataset for subsequent regional reservoir characterization studies
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".